A novel physical activity metric predicts cognitive and brain aging and ADRD risk

Project Summary
Low physical activity (PA) levels have been associated with elevated risk of Alzheimer’s dementia and
related disorders (ADRD). The bulk of this evidence has been derived from self-report measures of
PA and focused solely on PA volume and intensity. Objective PA assessment and quantifying
dynamics of continuous PA fluctuations over time using accelerometry may extend this area of
science by identifying early changes in functional capacity and emergent motor dysfunction, allowing
for a deeper understanding of how such changes are connected to brain aging and AD risk. We thus
developed a novel metric – “PA complexity” using the multiscale entropy (MSE) method to quantify
daily activity patterns by analyzing continuous accelerometer signals and apply this complexity
measure to a diverse older population in the Human Connectome Project – Connectomics in Brain
Aging and Dementia. This proposed study aims to (1) explore the associations between PA
complexity and cognitive function across multiple domains and risk of mild cognitive impairment (MCI)
and AD, (2) determine whether low PA complexity relates to AT(N) biomarker classifications and white
matter hyperintensities, (3) and examine whether low PA complexity is associated with brain atrophy.
This study is significant because (1) understanding the link between complexity of daily PA patterns,
cognitive function, and brain atrophy has the potential to yield new insights into the underlying
mechanisms connecting motor dysfunction to brain aging, (2) identifying altered complexity of activity
patterns as preclinical indicators of ADRD will suggest novel directions for tailored interventions to
further prevent or delay the onset of ADRD.

Grant Number: 5R03AG088612-02
NIH Institute/Center: NIH
Principal Investigator: Yurun Cai